Tag Archives: pitch f/x

Pitch f/x: Bonderman 4-3-08

From time to time this year (as time permits), I’ll delve in to MLB.com’s pitch f/x data to analyze a starters outing. Tonight we look at Jeremy Bonderman’s start against the Kansas City Royals on April 3rd.

Pitch Mix

This season MLB.com started classifying pitches. This seems pretty convenient, but from what I’ve seen so far the classifications don’t quite match. In the case of Jeremy Bonderman we know he throws both a 2 seam (sinker) and 4 seam fastball, a slider, and an occasional change. The data had Bonderman throwing a splitter, which looks to be a misclassification of his slider. Because of this, I did my own pitch classifications using K-means clustering and some judgment.

The table below shows his pitch mix and average velocity for the 87 pitches tracked by the system today.

	    n     mph
2seam       39   92.0 
4seam       25   92.6   
change       4   83.8  
slider      19   85.6   

Continue reading Pitch f/x: Bonderman 4-3-08

Scouting Bonderman with pitch f/x



Jim Leyland has come out on several occasions and said that Jeremy Bonderman is one of the keys to any success the Tigers might enjoy in 2008. Bonderman’s second half swoon, which I attribute largely to his elbow pain that he finally fessed up to, clouded what was starting out to be a phenomenal season. An ERA of 8.50 over his last 9 starts, combined with the arm troubles meant that Bonderman finished with the highest ERA and lowest innings total since his rookie season. Like with Dontrelle Willis, we’ll delve into the pitch f/x data and see what we can find out about the veteran 25 year old pitcher.
Continue reading Scouting Bonderman with pitch f/x

Scouting Dontrelle Willis

On Friday Lynn Henning wrote a detailed look at Dontrelle Willis with a heavy emphasis on scouting. I found the article fascinating from the stand point of getting a better understanding of Willis’s repertoire as well as the thought processes that went along with approving the deal for the lefty. He was after all coming off a pretty rough year. I also viewed it as a chance to dust off that pitch f/x database I’ve had sitting dormant and explore whether or not the reports meshed with what the system had reported.
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Fish Eye on the Tigers

Dan Fox at Baseball Prospectus recently did a post where he used the enhanced gameday (aka pitch/fx) data to categorize hitters by eye. He broke hitters down into the following groups and subsequently created some pretty slick graphs.

  • Square: This is the new metric, defined as the percentage of pitches in the strike zone swung at and made contact with. A high value here (relative to the average of over 87 percent) indicates that when the batter offers at a strike he usually makes contact. On the contrary, a lower value indicates hitters who, for reasons such as a long swing, are more apt to swing through strikes.
  • Fish: Defined as the percentage of pitches out of the strike zone that the hitter swung at. A higher percentage here indicates that the hitter may have trouble recognizing pitches since he is offering at pitches that would likely be called balls. Average values here are between 32 and 33 percent.
  • Bad Ball: Defined as the percentage of pitches out of the strike zone that were swung at where contact was made. This includes foul balls, although there is an argument to be made that a foul ball is not the intended outcome, and so should be discounted in some way. A higher value in this category indicates that, when swinging at bad pitches, the hitter is at least able to get the bat on the ball. Average values lie around 73 percent.
  • Eye: Defined as the percentage of pitches in the strike zone on non-three and zero counts that were taken for strikes. A smaller value in this metric indicates a player who recognizes strikes and aggressively offers at them. I excluded 3-0 counts, since a hitter is much more likely to let a strike go by in this situation, and we don’t want to penalize them for that behavior. Average values here are in the range of 25 to 27 percent.

While Detroit Tigers hitters were included in the analysis, it was tough to tease out exactly where they fell. Inspired, I thought I do the same analysis but focus on the Tigers. My numbers didn’t work out exactly the same as Fox’s, but the categorization of the players seemed to be fairly consistent. One reason for the disparity on the Eye metric is that the way I parse the data, I didn’t have the count readily available so I didn’t filter out taking on 3-0. The other discrepancy is probably the width of strike zone used. Fox said he used the 17 inch wide plate. Because only a portion of the ball has to cross the plate for a strike, I included the radius of the ball on either side of the plate as well. I’m also not sure how he included bunts and bunt attempts or being hit by a pitch. Regardless, the points remain the same.

As for the specifics on how the numbers differed, here are the league averages I calculated for each:

  • Square: 86%
  • Fish: 29%
  • Bad Ball: 70%
  • Eye: 36%

Fox then graphed Fish value against Eye values which put hitters into one of four categories. The graph of just the Tigers hitters is below:

Tigers batting eye

The first things that jump out in these types of graphs are the outliers. I don’t think that anyone is surprised that Pudge Rodriguez swings at more pitches out of the zone than anyone on the team. In fact, he swings at more than anyone in Major League Baseball.

What may surprise though is Sean Casey being in the lower left quadrant. Casey doesn’t strike out a whole lot, but he tends to swing at the bad pitches and take the good ones. The other surprise, especially given his strikeout rates, is Brandon Inge who is better than many of his peers in swinging at the pitches he should swing at and taking the ones he shouldn’t. Of course check swings where you go to far are still counted as swings so make of that what you will.

The last thing to notice is pretty much a team wide trend, and that is that the team tends to lean towards to the left, and that they are more likely than a typical team to chase pitches out of the zone. Even those players in the more patient hemisphere still are towards the middle. On a team level it confirms what pretty much everyone suspected based on observations.

The table below has the numbers for each of the Tigers:

Player			SQUARE	FISH	BADBALL	EYE
Brandon Inge 84% 27% 54% 35%
Cameron Maybin 80% 30% 40% 39%
Carlos Guillen 86% 32% 73% 20%
Curtis Granderson 89% 29% 63% 36%
Gary Sheffield 87% 27% 79% 42%
Ivan Rodriguez 81% 54% 77% 25%
Magglio Ordonez 88% 28% 76% 25%
Marcus Thames 73% 41% 63% 25%
Mike Hessman 82% 35% 65% 29%
Mike Rabelo 83% 34% 74% 17%
Omar Infante 84% 38% 79% 38%
Placido Polanco 96% 29% 89% 39%
Ramon Santiago 86% 43% 73% 26%
Ryan Raburn 77% 32% 60% 28%
Sean Casey 95% 39% 84% 43%
Timo Perez 88% 37% 84% 32%
Team 86% 33% 72% 32%

Baseball Prospectus | Articles | Schrodinger’s Bat: The Return of the Fish Eye

A different look at Andrew Miller

On Sunday, June 24th Andrew Miller took center stage on ESPN Sunday Night Baseball and promptly pitched 6 shut out innings. Miller only allowed 4 hits and 2 walks and was never really threatened. Was this a dominant performance by a young stud pitcher, or just another day at the office for the slumping Braves? I don’t know if we can really say one way or the other, but with enhanced gameday data we can at least get some additional information.
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Comparing Zumaya

A couple weeks ago we took a look at Joel Zumaya’s 2 inning save against Toronto through the eyes of MLB.com’s Enhanced Gameday. Last night against the White Sox Zumaya had an outing on the opposite end of the effectiveness spectrum.

Zumaya basically couldn’t find the strike zone to save his life last night. He through 32 pitches in one inning, and only 11 went for strikes. It resulted in 4 walks and a hit batter. Zumaya thought he was being squeezed.

zumayasz.jpg

Enhanced Gameday only captured 26 of Zumaya’s 32 pitches. Plotting them it does appear that Zumaya had a couple of pitches in the strike zone that were called balls. But there are also a ton of balls no where near the strike zone, and in general Joel was leaving the ball up.

Against Toronto, Joel was consistently on the edges of the strike zone. Against the White Sox he was erratic. Enhanced Game Day does allow us to take a look at one aspect of mechanics and that is release point.
Joel Zumaya release point comparison
While there is overlap in the clusters, it appears that Joel Zumaya was releasing the ball closer to the center of the mound. Now it is hard to say what, if anything this data means. The difference could be in the calibration of the cameras. Or perhaps Zumaya was working from a different part of the rubber Or it could be that his mechanics were altered and he was releasing the ball closer to his head against the White Sox.

In terms of velocity, of the 26 pitches that gameday captured, 23 were fastballs. Of those 23 fastballs only 10 topped 100mph so Zumaya was working a little under the velocity we saw in Toronto. Against the Jays he averaged 100.5 on the gun. Again, this could be a calibration issue, or it could be that Zumaya was never comfortable last night for one reason or another.

This data is still quite new, and I’m still learning to work with it. As we learn more about the data, and it’s limitations and strengths, hopefully we’ll be able to discern more.

A different look at the Bonderman-Halladay Duel

Taking advantage of the enhanced gameday data once again, I’ll take a look at Jeremy Bonderman’s and Roy Halladay’s awesome performances last night.

We’ll start with Jeremy Bonderman. The table below shows the mix of pitches and results for Bonderman:

It was a little surprising to see that Jeremy Bonderman didn’t miss that many bats last night, and none with his fastball. But what he did was induce a ton of weak contact. This was probably one of the biggest factors in keeping his pitch count so low.
Continue reading A different look at the Bonderman-Halladay Duel

A different look at Zumaya’s outing

I think everyone was mighty blown away by Joel Zumaya’s 2 inning save last night. He pounded the strike zone with 100mph plus heaters and buckled knees with his curve ball. But just for fun, and because we can, let’s take a look at all the pitches that made up his night.

I don’t know if you noticed in the playoffs last year, but MLB Gameday started using an enhanced version that had camera’s catching the path of the pitch, the velocity, and the release point. This was kind of a neat feature, but what makes it gold is that the data is captured and stored on MLB.com’s servers. Inspired by the book Baseball Hacks: Tips & Tools for Analyzing and Winning with Statistics, and with some programming of my own, I worked this offseason to be able to capture and analyze this data. Imagine my disappointment when after the first 8 games the Tigers hadn’t had an “enhanced” game. Fortunately they did last night.
Continue reading A different look at Zumaya’s outing